371 lines
13 KiB
C
371 lines
13 KiB
C
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#ifndef ANSFRCOMMON_H
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#define ANSFRCOMMON_H
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#define ANSF_API __declspec(dllexport)
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#pragma once
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#include <fstream>
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#include <iostream>
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#include <string>
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#include <vector>
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#include <opencv2/core.hpp>
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#include <opencv2/imgproc.hpp>
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#include "NvInfer.h"
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//#include <cublasLt.h>
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#include "ANSLicense.h"
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#include "LabVIEWHeader/extcode.h"
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#include "Utility.h"
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#include "macros.h"
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#include "ANSEngineCommon.h"
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#include "openvino/openvino.hpp"
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using namespace nvinfer1;
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#define CUDACHECK(status) \
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do\
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{\
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auto ret = (status);\
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if (ret != 0)\
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{\
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std::cerr << "Cuda failure: " << ret << std::endl;\
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abort();\
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}\
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} while (0)
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namespace ANSCENTER {
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struct UserRecord {
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int UserId;
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std::string UserCode;
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std::string UserName;
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std::vector<int> FaceIds;
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};
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struct FaceRecord {
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int FaceId;
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int UserId;
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std::string ImagePath;
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};
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struct alignas(float) Detection {
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float bbox[4]; //x1 y1 x2 y2
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float class_confidence;
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float landmark[10];
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};
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struct CroppedFace {
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cv::Mat face;
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cv::Mat faceMat;
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int x1, y1, x2, y2;
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};
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struct Bbox {
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int x1, y1, x2, y2;
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float score;
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};
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struct Paths {
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std::string absPath;
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std::string className;
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};
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struct AnchorBox {
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float cx;
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float cy;
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float sx;
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float sy;
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};
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struct FRConfig {
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std::string _databasePath;
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int _videoFrameWidth;
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int _videoFrameHeight;
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std::string _detEngineFile;
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std::vector<int> _detInputShape;
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std::string _detInputName;
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std::vector<std::string> _detOutputNames;
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int _detMaxBatchSize;
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float _detThresholdNMS;
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float _detThresholdBbox;
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std::vector<int> _recInputShape;
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int _recOutputDim;
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std::string _recEngineFile;
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int _maxFacesPerScene;
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float _knownPersonThreshold;
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int _recMaxBatchSize;
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std::string _recInputName;
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std::string _recOutputName;
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bool _gen;
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std::string _gen_imgSource;
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bool _gen_imgIsCropped;
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bool _apiImageIsCropped;
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};
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struct HeadPoseResults {
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float angle_r;
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float angle_p;
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float angle_y;
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};
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struct AgeGenderResults {
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float age;
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float maleProb;
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};
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//// Class for face attribute
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class ANSF_API Face {
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public:
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//using Ptr = std::shared_ptr<Face>;
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explicit Face(size_t id, cv::Rect& location);
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void updateAge(float value);
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void updateGender(float value);
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void updateEmotions(std::map<std::string, float> values);
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void updateHeadPose(HeadPoseResults values);
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void updateLandmarks(std::vector<float> values);
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void updateRealFaceConfidence(float value);
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void updateFaceLiveness(int value);
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int getAge();
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bool isMale();
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bool isReal();
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float getAntispoofingScore();
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int getFaceLiveness();
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std::map<std::string, float> getEmotions();
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std::pair<std::string, float> getMainEmotion();
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HeadPoseResults getHeadPose();
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const std::vector<float>& getLandmarks();
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size_t getId();
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void ageGenderEnable(bool value);
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void emotionsEnable(bool value);
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void headPoseEnable(bool value);
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void landmarksEnable(bool value);
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void antispoofingEnable(bool value);
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void faceLivenessEnable(bool value);
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bool isAgeGenderEnabled();
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bool isEmotionsEnabled();
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bool isHeadPoseEnabled();
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bool isLandmarksEnabled();
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bool isAntispoofingEnabled();
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bool isFaceLivenessEnabled();
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public:
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cv::Rect _location;
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float _intensity_mean;
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private:
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size_t _id;
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float _age;
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float _maleScore;
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float _femaleScore;
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std::map<std::string, float> _emotions;
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HeadPoseResults _headPose;
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std::vector<float> _landmarks;
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float _realFaceConfidence;
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int _faceLiveness;
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bool _isAgeGenderEnabled;
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bool _isEmotionsEnabled;
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bool _isHeadPoseEnabled;
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bool _isLandmarksEnabled;
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bool _isAntispoofingEnabled;
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bool _isFaceLivenessEnabled;
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};
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class ANSF_API BaseDetection {
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public:
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BaseDetection(const std::string& pathToModel, bool doRawOutputMessages);
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virtual ~BaseDetection() = default;
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virtual std::shared_ptr<ov::Model> read(const ov::Core& core) = 0;
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bool enabled() const;
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ov::InferRequest request;
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ov::Tensor inTensor;
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std::string pathToModel;
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ov::Shape inShape;
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const bool doRawOutputMessages;
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};
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class ANSF_API HeadPoseDetection :public BaseDetection {
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public:
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std::recursive_mutex _mutex;
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std::string outputAngleR;
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std::string outputAngleP;
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std::string outputAngleY;
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std::string _modelFilePath;
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//size_t enquedFaces;
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cv::Mat cameraMatrix;
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HeadPoseDetection(const std::string& pathToModel, bool doRawOutputMessages);
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virtual std::shared_ptr<ov::Model> read(const ov::Core& core) override;
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HeadPoseResults runInfer(const cv::Mat& frame);
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//void submitRequest();
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//void enqueue(const cv::Mat& face);
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//HeadPoseResults getResult(int idx);
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//std::vector<HeadPoseResults> getAllResults();
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};
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class ANSF_API AgeGenderDetection :public BaseDetection {
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public:
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std::recursive_mutex _mutex;
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std::string outputAge;
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std::string outputGender;
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//size_t enquedFaces;
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std::string _modelFilePath;
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AgeGenderDetection(const std::string& pathToModel,
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bool doRawOutputMessages);
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virtual std::shared_ptr<ov::Model> read(const ov::Core& core) override;
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AgeGenderResults runInfer(const cv::Mat& frame);
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//void submitRequest();
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//void enqueue(const cv::Mat& face);
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//AgeGenderResults getResult(int idx);
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//std::vector<AgeGenderResults> getAllResults();
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};
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class ANSF_API EmotionsDetection : public BaseDetection {
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public:
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std::recursive_mutex _mutex;
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//size_t enquedFaces;
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std::string _modelFilePath;
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const std::vector<std::string> emotionsVec = { "neutral", "happy", "sad", "surprise", "anger" };
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EmotionsDetection(const std::string& pathToModel,
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bool doRawOutputMessages);
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virtual std::shared_ptr<ov::Model> read(const ov::Core& core) override;
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std::map<std::string, float> runInfer(const cv::Mat& frame);
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//void submitRequest();
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//void enqueue(const cv::Mat& face);
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//std::map<std::string, float> getResult(int idx);
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//std::vector<std::map<std::string, float>> getAllResults();
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};
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class FacialLandmarksDetection : public BaseDetection {
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public:
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//size_t enquedFaces;
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std::vector<std::vector<float>> landmarks_results;
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std::vector<cv::Rect> faces_bounding_boxes;
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std::string _modelFilePath;
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std::recursive_mutex _mutex;
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FacialLandmarksDetection(const std::string& pathToModel,
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bool doRawOutputMessages);
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virtual std::shared_ptr<ov::Model> read(const ov::Core& core) override;
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std::vector<float> runInfer(const cv::Mat& frame);
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//void submitRequest();
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//void enqueue(const cv::Mat& face);
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//std::vector<float> getResult(int idx);
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};
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class ANSF_API AntispoofingClassifier : public BaseDetection {
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public:
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std::recursive_mutex _mutex;
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//size_t enquedFaces;
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std::string _modelFilePath;
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AntispoofingClassifier(const std::string& pathToModel,bool doRawOutputMessages);
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virtual std::shared_ptr<ov::Model> read(const ov::Core& core) override;
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float runInfer(const cv::Mat& frame);
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//void submitRequest();
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//void enqueue(const cv::Mat& frame);
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//float getResult(int idx);
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};
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class ANSFRHelper {
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public:
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static unsigned char* CVMatToBytes(cv::Mat image, unsigned int& bufferLengh);
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static void GetCroppedFaces(const cv::Mat& input, std::vector<Object>& outputBbox, int resize_w, int resize_h, std::vector<struct CroppedFace>& croppedFaces);
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static void GetFilePaths(std::string rootPath, std::vector<struct Paths>& paths);
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static bool LoadConfigFile(std::string configFile, FRConfig& config);
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static std::string StringCurrentDateTime(); // Return current datetime in string format
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static std::string FaceObjectsToJsonString(const std::vector<FaceResultObject>& faces);
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static cv::Mat PreprocessImg(cv::Mat& img, int inputW, int inputH);
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static int ReadFilesInDir(const char* pDirName, std::vector<std::string>& fileNames);
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static cv::Rect GetRectAdaptLandmark(cv::Mat& img, int inputW, int inputH, float bBox[4], float lmk[10]);
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static float IOU(float lbox[4], float rbox[4]);
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static bool CMP(const Detection& a, const Detection& b);
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static void NMS(std::vector<Detection>& res, float* output, float nms_thresh = 0.4);
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static std::map<std::string, Weights> LoadWeights(const std::string file);
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static Weights GetWeights(std::map<std::string, Weights>& weightMap, std::string key);
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static IScaleLayer* AddBatchNorm2D(INetworkDefinition* network, std::map<std::string, Weights>& weightMap, ITensor& input, std::string lName, float eps);
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static std::string UserRecordToJsonString(const UserRecord userRecord);
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static std::string UserRecordsToJsonString(const std::vector<UserRecord> userRecords);
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static std::string FaceRecordToJsonString(const FaceRecord faceRecord);
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static std::string FaceRecordsToJsonString(const std::vector<FaceRecord> faceRecords);
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static std::string FaceAttributeToJsonString(Face face);
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};
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float calcIoU(cv::Rect& src, cv::Rect& dst);
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float calcMean(const cv::Mat& src);
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Face matchFace(cv::Rect rect, std::list<Face>& faces);
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// Class to extend TensorRT logger
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/* class TRTLogger : public nvinfer1::ILogger {
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public:
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void log(Severity severity, const char* msg) noexcept override {
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if (severity <= Severity::kWARNING) {
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std::cout << "TENSORRT_ENGINE:" << msg << std::endl;
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}
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}
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void LogDebug(const std::string source, std::string message) {
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std::cout << source << ":" << message << std::endl;
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}
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void LogInfo(const std::string source, std::string message) {
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std::cout << source << ":" << message << std::endl;
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}
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void LogError(const std::string source, std::string message) {
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std::cout << source << ":" << message << std::endl;
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}
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void LogFatal(const std::string source, std::string message) {
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std::cout << source << ":" << message << std::endl;
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}
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~TRTLogger() {
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}
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};
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class MatMul {
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public:
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MatMul();
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~MatMul();
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void Init(float* knownEmbeds, int numRow, int numCol);
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void Calculate(float* embeds, int embedCount, float* outputs);
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private:
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cudaDataType_t cudaDataType = CUDA_R_32F;
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cublasComputeType_t computeType = CUBLAS_COMPUTE_32F;
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cublasLtHandle_t ltHandle;
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cublasOperation_t transa = CUBLAS_OP_T;
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cublasOperation_t transb = CUBLAS_OP_N;
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void* workspace;
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const size_t workspaceSize = 1024 * 1024 * 4;
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cudaStream_t stream;
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float* dA, * dB, * dC;
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const float alpha = 1, beta = 0;
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int m, n, k, lda, ldb, ldc;
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cublasLtMatmulDesc_t operationDesc = NULL;
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cublasLtMatrixLayout_t Adesc = NULL;
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cublasLtMatmulPreference_t preference = NULL;
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};
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class Int8EntropyCalibrator2 : public nvinfer1::IInt8EntropyCalibrator2
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{
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public:
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Int8EntropyCalibrator2(int batchsize, int input_w, int input_h, const char* img_dir, const char* calib_table_name, const char* input_blob_name, bool read_cache = true);
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virtual ~Int8EntropyCalibrator2();
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int getBatchSize() const TRT_NOEXCEPT override;
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bool getBatch(void* bindings[], const char* names[], int nbBindings) TRT_NOEXCEPT override;
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const void* readCalibrationCache(size_t& length) TRT_NOEXCEPT override;
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void writeCalibrationCache(const void* cache, size_t length) TRT_NOEXCEPT override;
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private:
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int batchsize_;
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int input_w_;
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int input_h_;
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int img_idx_;
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std::string img_dir_;
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std::vector<std::string> img_files_;
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size_t input_count_;
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std::string calib_table_name_;
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|
const char* input_blob_name_;
|
||
|
|
bool read_cache_;
|
||
|
|
void* device_input_;
|
||
|
|
std::vector<char> calib_cache_;
|
||
|
|
};*/
|
||
|
|
}
|
||
|
|
#endif
|